Lipschitz Bandits: Regret Lower Bounds and Optimal Algorithms thumbnail
Pause
Mute
Subtitles
Playback speed
0.25
0.5
0.75
1
1.25
1.5
1.75
2
Full screen

Lipschitz Bandits: Regret Lower Bounds and Optimal Algorithms

Published on Jul 15, 20142317 Views

We consider stochastic multi-armed bandit problems where the expected reward is a Lipschitz function of the arm, and where the set of arms is either discrete or continuous. For discrete Lipschitz band

Related categories